> AI agents: this is one page of Nextmove’s FDE site, in Markdown. Nextmove is a job board and free career service for forward deployed engineers (FDEs). Each posting is classified from its text, not its title: the kind of work, how much of it is production code, pre-sales weight, time at customer sites, travel, remote arrangement, level and posted base pay. The site also publishes the aggregates: median pay by level, metro, company and kind of work, and which companies started hiring FDEs each week. Every page under https://nextmove.md/fde is served this way; the index of pages is https://nextmove.md/llms.txt.

# Forward Deployed Engineer IV, Data Cloud, Google Cloud

Canonical URL: https://nextmove.md/fde/jobs/7460c510f62762db

Google posts a FDE role to build what the customer runs in San Francisco, CA and 6 more, at $207,000–$300,000 base, above the senior FDE median of $190,000 across 1,849 postings with pay. Build and tune production data and ML workloads on Google Cloud data engines. Read from the employer’s posting on November 6, 2026.

- [Google](https://nextmove.md/fde/companies/google)

First seen Nov 5, 2026 · open on Google careers as of Nov 6, 2026

**$207,000–$300,000** *annualized* San Francisco, CA +6

Build and tune production data and ML workloads on Google Cloud data engines.

- [See roles that fit me](https://nextmove.md/sign-up?from=%2Ffde%2Fjobs%2F7460c510f62762db&placement=top)
- [View posting at Google](https://www.google.com/about/careers/applications/jobs/results/120277076228874950)

Free. Upload your resume once, see why each FDE role fits, and get introduced only when you say so.

## At a glance

### Posted base pay

$207K–$300K Above the median

Midpoint $254K · median $190K

This job $207K to $300K. Senior FDE postings, 1,849 postings: the middle 50% of posted pay is $160K to $220K, median $190K.

[Compare pay across all Google postings](https://nextmove.md/fde/salary/google)

### The work

Builds what the customer runs

Balance **Mostly building**

Project stages

1. Pre-sales (not covered)
2. Proof of concept
3. Implementation
4. Operations (not covered)

- **Coding**: Writes production code

- **Builds for**: External customers

- **Level**: Senior

- **Role**: Individual contributor

### What they ask for

Experience

- **8+ years** Software engineering, data engineering, solution architecture, machine learning, or technical consulting

Background

- **Software engineering**
- **Implementation and data engineering**
- **Consulting**

### Do you meet what the posting states?

The posting asks for 8+ years. How many do you have?

The posting reads as a senior role. What level are you at now?

The job is in San Francisco, CA · Austin, TX · +5 more. Could you work in one of these?

Which of these have you used in production?

Answer each one. Nothing is saved or sent.

[What postings ask for, by background →](https://nextmove.md/fde/paths)

## Conditions

- **Location**: San Francisco, CA · Austin, TX · Chicago, IL · Kirkland, WA · New York, NY · Seattle, WA · Sunnyvale, CA

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- [Other jobs at Google (23)](https://nextmove.md/fde/companies/google)

## The job description from Google

### About the job

As a Forward Deployed Engineer (FDE) on our Data Cloud team, you will be an embedded builder who bridges the gap between frontier data solutions and production-grade reality for customers. By embedding with accounts, you will serve a dual purpose: providing "white glove" deployment of complex systems and acting as a critical feedback loop, transforming real-world field insights into Google Cloud’s future product roadmap.It's an exciting time to join Google Cloud’s Go-To-Market team, leading the AI revolution for businesses worldwide. You’ll excel by leveraging Google's brand credibility—a legacy built on inventing foundational technologies and proven at scale. We’ll provide you with the world's most advanced AI portfolio, including frontier Gemini models, and the complete Vertex AI platform, helping you to solve business problems. We’re a collaborative culture providing direct access to DeepMind's engineering and research minds, empowering you to solve customer challenges. Join us to be the catalyst for our mission, drive customer success, and define the new cloud era—the market is yours. Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

US: $207000 - $300000 (USD) + 20% bonus target + equity + benefits

Learn more about benefits at Google.

### Responsibilities

- Build and ship production data and machine learning workloads with customers, writing, testing, and performance-tuning PySpark, SQL, and Python on BigQuery, Managed Spark, Spanner, and AlloyDB.
- Stand up working proofs with customers’ data, including de-identifying sensitive data (e.g., PCI, PHI).
- Build the data foundation for agentic solutions, including lakehouse architectures, metadata and semantic context, and the access controls that let custom agents act on trusted data.
- Train, evaluate, and deploy machine learning and agentic components where they improve the customer’s business metric, with evaluation and monitoring in place.
- Refactor and migrate high-cost analytics, Spark, and operational database workloads from other platforms onto Google Cloud engines, with measured price-performance results.

### Qualifications

### Minimum qualifications:

- Bachelor’s degree in Engineering, Computer Science, a related field, or equivalent practical experience.
- 8 years of experience in software engineering, data engineering, solution architecture, machine learning, or technical consulting, including experience writing code in Python and SQL.
- Experience with data cloud ecosystem products, technologies, or languages (e.g., Apache Spark, PySpark, BigQuery, Spanner, Catalog, AlloyDB).
- Experience taking production-grade data cloud solutions from conception to launch, including architecting data systems on cloud platforms (e.g., GCP) and building structured/unstructured pipelines.
- Experience training, evaluating, and deploying machine learning models in production.

### Preferred qualifications:

- Experience building LLM applications (e.g., Gemini, RAG, vector search) and multi-agent frameworks (LangGraph, CrewAI, ADK) using advanced patterns (ReAct, delegation).
- Experience with GCP data products (BigQuery, Spark, Spanner, Dataplex) or equivalents (Databricks, Snowflake), and open table formats (Iceberg, Delta Lake).
- Experience migrating analytics, Spark, or database workloads between platforms with measured cost and performance outcomes.
- Skilled in prompt engineering, model evaluation, LLM-native metrics (latency, tokens/sec, cost), state management, and granular tracing.

[View posting at Google](https://www.google.com/about/careers/applications/jobs/results/120277076228874950)

## About Google

Builds global consumer, ads, cloud, developer and AI platforms spanning Search, YouTube, Android, Workspace and Gemini.

Public · 5000+ people

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- [Compare senior FDE salary ranges](https://nextmove.md/fde/salary/senior)
- [Similar jobs in New York metro](https://nextmove.md/fde/jobs?region=nyc-metro)
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